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The Sentiment Cascade: A sequential structure from earnings calls through media and investors to market reaction

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  • Ho, Chuan-Chun
  • Chang, Dong-Shang

Abstract

This study examines how sentiment following earnings call events is structured across layers and aligned with short-term market reaction. Existing studies remain fragmented in system coverage and structural specification. To address these gaps, we propose the Sentiment Cascade Model (SCM), which specifies a sequential configuration linking earnings call sentiment, media sentiment, investor sentiment, and market reaction. Using a large sample of S&P 500 earnings calls, we estimate the SCM via structural equation modeling and compare it with parallel and reverse alternatives. The sequential configuration exhibits superior overall model fit (CFI = 0.996; RMSEA = 0.020). Crucially, the direct linkage from earnings call sentiment to market reaction indicates that the sequential configuration is not jointly sufficient to account for market reaction, highlighting the independent structural role of the original disclosure. The findings may inform future research adopting causal identification designs.

Suggested Citation

  • Ho, Chuan-Chun & Chang, Dong-Shang, 2026. "The Sentiment Cascade: A sequential structure from earnings calls through media and investors to market reaction," Research in International Business and Finance, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:riibaf:v:89:y:2026:i:c:s0275531926001935
    DOI: 10.1016/j.ribaf.2026.103466
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